SONG Qian,ZHANG Guo-qing,HUANG Nan,et al.Leaf Area Index Inversion Based on the Environmental Satellite Data[J].HEILONGJIANG AGRICULTURAL SCIENCES,2013,(07):136-140.
基于环境减灾小卫星数据叶面积指数的反演
- Title:
- Leaf Area Index Inversion Based on the Environmental Satellite Data
- 文章编号:
- 1002-2767（2013）07-0136-05
- 分类号:
- S127
- 文献标志码:
- A
- 摘要:
- 叶面积指数是反映农田信息的重要参数之一，因此获取叶面积指数成为农情遥感的一项重要内容。利用田间实测调查数据,系统分析了环境星的归一化植被指数（NDVI）与宾县地区主要作物玉米和水稻叶面积指数的关系,并采用简单线性模型、多项式模型和对数模型建立作物叶面积指数的估算模型进行最优反演。结果表明:玉米和水稻叶面积指数的最优反演模型都采用多项式模型，精度分别达到了0.805和0.810，并采用该模型进行反演。
- Abstract:
- The leaf area index(LAI)is one of the most important parameters that reflect the farmland information.Therefore,LAI play an important role in the situation of agricultural remote sensing.Basing on field survey data,the correlations between the HJ-CCD data and the parameters of maize and rice in Bin county were systematically analyzed,and by adopting LAI estimation models,including simple linear model,polynomial model and logistic model,optimal inversion were conducted.The results showed that NDVI had the greatest correlation with LAI,suggesting that the HJ-CCD data could be used to estimate LAI of maize and rice.Among the three models,the polynomial model could greatly reduce LAI estimation error,with the accuracy reached 0.805-,and 0.810.
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备注/Memo
收稿日期：2013-03-25
第一作者简介：宋茜（1985-），女，山西省太原市人，硕士，研究实习员，从事农业遥感研究。E-mail：maomiwin999@sina.com。